Perbandingan Skema Dekomposisi Paket Wavelet untuk Pengenalan Sinyal EKG
Abstract
One indicator of a person's health is signal pattern of electrocardiogram (ECG). ECG signals are generated by the heart's electrical activity. ECG signal pattern is recognized by physicians to determine a patient's heart health. Some of the techniques were developed by researchers to automatically recognize the ECG signal. One of the most popular techniques is wavelet transform. In this study, two wavelet packet decomposition schemes for ECG signal recognition are compared to find the best one. The first scheme generates 32 features while the second scheme generates 15 features. Accuracy testing shows that the first scheme produce the best average accuracy of 94.67%, better than the second scheme. Using features selection on the first scheme, four dominant features that produce higher accuracy than using 32 features are obtained. These results indicate that the first scheme is better than the second scheme for ECG signal recognition using wavelet packet decomposition.
References
W. J. Tompkins, “Electrocardiography,” in Biomedical Digital Signal Processing, W. J. Tompkins, Ed. New Jersey: Prentice Hall, 2000, pp. 24–54.
J. L. Schuster, C. Spence, M. Jacobs, and A. Wilkonson, “Living with Advanced Congestive Heart Failure : A Guide for Family Caregivers,” 2002.
S. M. Al-khatib, N. A. Lapointe, and R. Chatterjee, “Treatment of Atrial,” Comp. Eff. Rev., no. 119, 2013.
B. S. Kim, S. K. Yoo, and M. H. Lee, “Wavelet-Based Low-Delay ECG Compression Algorithm for Continuous ECG Transmission,” Ieee Trans. Inf. Technol. Biomed., vol. 10, no. 1, pp. 77–83, 2006.
E. Alexandre, A. Pena, and M. Sobreira, “On the Use of 2-D Coding Techniques for ECG Signals,” Ieee Trans. Inf. Technol. Biomed., vol. 10, no. 4, pp. 809–811, 2006.
V. B. Romero, “ECG baseline wander removal and noise suppression analysis in an embedded platform,” Universidad Complutense de Madrid, 2009.
S. Z. Mahmoodabadi, A. Ahmadian, and M. D. Abolhasani, “ECG Feature Extraction Using Daubechies Wavelets,” in Proc. of the fifth IASTED International Conference Visualization, Imaging, and Image Processing, 2005, vol. 2, no. 2, pp. 343–348.
C. Saritha, V. Sukanya, and Y. N. Murthy, “ECG Signal Analysis Using Wavelet Transforms,” Bulg. J. Phys., vol. 35, pp. 68–77, 2008.
A. Rizal and V. Suryani, “Pengenalan signal ekg menggunakan dekomposisi paket wavelet dan k-means-clustering,” in Proceeding Seminar Nasional Aplikasi Teknologi Inofrmasi 2008(SNATI 2008), 2008, vol. 2008, no. Snati, pp. 5–8.
L. Brechet, M. Lucas, C. Doncarli, and D. Farina, “Compression of Biomedical Signals with Mother Wavelet Optimization and Best-Basis Wavelet Packet Selection,” IEEE Trans. Biomed. Eng., vol. 54, no. 12, pp. 2186 – 2192, 2007.
A. Surtono, T. S. Widodo, and M. Tjokronagoro, “Analisis Klasifikasi Sinyal EKG Berbasis Wavelet dan Jaringan Syaraf Tiruan,” J. Nas. Tek. Elektro dan Teknol. Inf., vol. 1, no. 3, pp. 60–66, 2012.
A. Rizal, T. L. R. Mengko, and A. B. Suksmono, “Lung Sound Recognition Using Wavelet Packet Decomposition and ART2 ( Adaptive Resonance Theory 2 ) Neural Network,” in Proceeding Biomedical Engineering Day 2006, 2006, vol. 2, pp. 2–6.
A. Rizal, “Wrapper Features Subset Selection Pada Ekstraksi Ciri Sinyal EKG Menggunakan Metode Dekomposisi Paket Wavelet,” J. Inform., vol. 8, no. 2, pp. 105–114, 2012.
Physionet.org, “ECG Database.” [Online]. Available: http://physionet.org/physiobank/database/#ecg.
E. A. Ashley and J. Niebauer, “Conquering the ECG - Cardiology Explained - NCBI Bookshelf,” in Cardiology Explained, London: Remedica, 2004.
M. Kociolek, A. Materka, M. Strzelecki, and P. Szezypinski, “Discrete Wavelet Transform – Derived Features for Digital Image Texture Analysis,” in Proceeding of International Conference and Electronics System, 2001, no. September, pp. 163–168.
R. Palaniappan, Biological Signal Analysis. Ventus Publishing ApS, 2010, p. 117.
S. Reichert, R. Gass, C. Brandt, and E. Andrès, “Analysis of Respiratory Sounds : State of the Art,” Clin. Med. Circ. Respir. Pulm. Med., vol. 2, pp. 45–58, 2008.
A. Goshtasby, Image Registration, Priciples, Tools and Methods, First. Springer-Verlag London Limited, 2012.
© Jurnal Nasional Teknik Elektro dan Teknologi Informasi, under the terms of the Creative Commons Attribution-ShareAlike 4.0 International License.
1.png)
